Fiducial inference was introduced in the first half of the 20th century by Fisher (1935) as a means to get a posterior-like distribution for a parameter without having to arbitrarily define a prior. While the method originally fell out of favor due to non-exactness issues in multivariate cases, the method has garnered renewed interest in the last decade. This is partly due to the development of generalized fiducial inference, which is a fiducial perspective on generalized confidence intervals: a method used to find approximate confidence distributions. In this chapter, we illuminate the usefulness of the fiducial philosophy, introduce the definition of a generalized fiducial distribution, and apply it to interesting, non-trivial inferential examples.
翻译:费舍尔(1935年)在20世纪上半叶引入了纤维推断法,作为在无需任意界定先前参数的情况下获得类似参数的后方分布的方法。虽然这种方法最初由于多变情况中的非精确性问题而失去优势,但在过去十年中又重新引起了兴趣。这在一定程度上是由于普遍纤维推断法的发展,这是对普遍信任间隔的一种理解:一种用来寻找大致信任分布的方法。 在本章中,我们阐明了纤维哲学的用处,引入了普遍纤维分布的定义,并将其应用于有趣的、非三联推断的例子。</s>